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%% README %JD Coutinho, P Lefevre, G Blohm 2019 ([email protected]) % Confidence in predicted position error explains saccadic decisions during pursuit % doi: https://doi.org/10.1101/396788 %% Introduction %The files contained within simulate 1D visual tracking (pursuit and saccadic eye movements) to simulated target motion % To replicate manuscript findings, the main scripts are: % Simulate_SingleTrials.m --> Fig 4, 6 % Simulate_Experiment.m --> Fig 5, 7, 9, 10 % Simulate_PhasePlot.m --> Fig 8 % Plot_ParamVariations.m --> Fig 11 % (Fig 1-2, model block diagrams; Fig 3. Saccade Decision Schematic Diagram) % To quickly replicate Figs, % Load pre-simulated data % Fig 5 --> Plot_bieg.m(SummaryData_bieg, Params_bieg) % Fig 7 --> Plot_deBrouwer3(SummaryData_txt, Params_txt) % Fig 9 --> Plot_deBrouwer2(SummaryData_txt, Params_txt) % Fig 10 --> Plot_SRTdistributions(SummaryData, Params), txt or BLUR %% Contents % This directory should have 3 folders: Functions, Scripts, Simulation Data %Functions % %Plotting Functions % Plot_bieg.m % Plot_deBrouwer2.m % Plot_deBrouwer3.m % Plot_SingleTrials.m % Plot_SRT_SaccProp.m % Plot_SRTdistributions.m %(external): % brewermap.m % ciplot.m % linspecer.m % boundedline package %Colormaps package % %Model Functions % Calculate_SaccadeMetrics.m % Catch_up_saccade.m % Find_conditionVector.m % Find_SaccadeMetrics2.m % Initialize_DecisionParams.m % Initialize_DefaultTriggerModel.m % Initialize_KalmanParams.m % Initialize_MotorParams.m % Initialize_SimulationSignals.m % Initialize_TrialParams.m % KalmanFilter2_PE.m % KalmanFilter2_RS.m % KalmanFilter2_RA.m % LeakyIntegrator.m % PEpredict.m % RSpredict.m % PursuitMotionPathway.m % SaccDecisionLLR.m % Simulate_FullExpt.m % Simulate_TargetMotion.m % Simulate_TargetMotion2.m % Simulate_VisTracking.m %Scripts % Plot_ParamVariations.m % Simulate_Experiment.m % Simulate_PhasePlot.m % Simulate_SingleTrials.m %Simulation Data % SaccConfidencePhasePlot.mat % SimData_bieg.mat % SimData_txt.mat % SimData_txt_BLUR.mat
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